Chloride Insertion–Immobilization Enables Bright, Narrowband, and Stable Blue-Emitting Perovskite Diodes
Bibliographic record
Abstract
Metal halide perovskites show promise for light-emitting diodes (LEDs) owing to their facile manufacture and excellent optoelectronic performance, including high color purity and spectral stability, especially in the green region. However, for blue perovskite LEDs, the emission spectrum line width is broadened to over 25 nm by the coexistence of multiple reduced-dimensional perovskite domains, and the spectral stability is poor, with an undesirable shift (over 7 nm) toward longer wavelengths under operating conditions, degradation that occurs due to phase separation when mixed halides are employed. Here we demonstrate chloride insertion-immobilization, a strategy that enables blue perovskite LEDs, the first to exhibit narrowband (line width of 18 nm) and spectrally stable (no wavelength shift) performance. We prepare bromide-based perovskites and then employ organic chlorides for dynamic treatment, inserting and in situ immobilizing chlorides to blue-shift and stabilize the emission. We achieve sky-blue LEDs with a record luminance over 5100 cd/m 2 at 489 nm, and an operating half-life of 51 min at 1500 cd/m 2 . By device structure optimization, we further realize an improved EQE of 5.2% at 479 nm and an operating half-life of 90 min at 100 cd/m 2 .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".